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\section{Results and Evaluation}
\label{sec:results}
In this section, we present our generated model and evaluate its performance.

\subsection{Methodology}
In order to evaluate performance, we decided to aim for high accuracy and
recall for positive examples. We discovered that this data set has low signal
for identifying positive examples, so the models produced by the SVMs would
typically choose all or most of the examples to be negative and achieve at
least $66$\% accuracy. Consequently, we strived for high recall on positive
examples so that our models produced useful data when they did produce
outcomes.

\begin{tabular}{|c|c|c|}
                                        \hline
            & true false & true true \\ \hline
pred. false & \fix{num}  & \fix{num} \\ \hline
pred. true  & \fix{num}  & \fix{num} \\ \hline
\end{tabular}
\label{tab:linear}
